Fuzzy-neural sliding mode controller and its application to the vehicle anti-lock braking systems.

摘要

One of the major problems in designing the controller for the vehicle anti-lock braking systems is finding the appropriate control algorithms to rejecting the parameter uncertainties such as friction coefficient, road elevation, wind gust, road superelevation, vehicle absolute speed, and so on. A new class of algorithms is developed by combining sliding mode control technique and fuzzy logic control theory with artificial neural networks to achieve the following things: The most important function of the vehicle anti-lock braking controller is to provide the vehicle with sufficient stopping ability without sacrificing the vehicle stability and the steerability. The proposed controller outperforms fuzzy-sliding mode controller and feedback linearization and sliding mode controllers. The proposed fuzzy-neural-sliding mode controller shows that the performance of the vehicle ABS systems has been improved when fuzzy-sliding mode controller was combined with artificial neural networks since artificial neural networks have abilities such as learning, adaptation, and so on.